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  1. GEO (View Publication)
    Full Name of the Resource : Gene Expression Omnibus: Public gene expression repository
    Resource Category : Databases -> Microarray Data and Gene Expression Databases -> Microarray Data and other Gene Expression Databases

    Brief Description : GEO serves as a public repository for a wide range of high-throughput experimental data. These data include single and dual channel microarray-based experiments, measuring the abundance of mRNA, genomic DNA and protein molecules. Data from non-array-based high-throughput functional genomics and proteomics technologies are also archived, including serial analysis of gene expression (SAGE) and protein identification technology. Several tools are provided to assist with the visualization and exploration of GEO data, including hierarchical cluster heat maps and searchable individual gene expression profiles. Suitable GEO records are assembled into biologically and statistically comparable datasets. These datasets are then indexed and loaded into Entrez GEO Profiles and Entrez GEO DataSets, which allows users to query and analyze the data using simple boolean queries, and provides links to other NCBI resources wherever possible (e.g. sequence, publication and genomic mapping). GEO is available on the World Wide Web at http://www.ncbi.nlm.nih.gov/geo/. GEO DataSets may be browsed at http://www.ncbi.nlm.nih.gov/geo/gds/gds_browse.cgi or searched by keywords at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gds . GEO Profiles are searchable at (3) http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=geo. All these tools are intralinked and accessible from the GEO home page.

    Institute/s :
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
    Country : United States

    Associated Institutes :

    • National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD 20892, USA

    Associated Country : USA


    Year : 2011

    Keywords : Algorithms; Cluster Analysis; Computational Biology / *methods; Computers; Data Interpretation, Statistical; Databases, Factual; Databases, Genetic; *Gene Expression Profiling; Information Storage and Retrieval; *Oligonucleotide Array Sequence Analysis; Programming Languages; Software